AliAmini93/TelecomSent
Developed BERT, LSTM, TFIDF, and Word2Vec models to analyze social media data, extracting service aspects and sentiments from a custom dataset. Provided actionable insights to telecom operators for customer satisfaction and competitive analysis.
This project helps telecom operators understand what customers are saying about their services and competitors on Twitter and Facebook. It takes social media posts as input and identifies specific service aspects (like network quality or customer service) and the sentiment (positive, negative, neutral) expressed towards them. The output provides structured insights that marketing and customer experience teams can use.
No commits in the last 6 months.
Use this if you are a telecom operator who wants to automatically analyze social media data to pinpoint customer pain points, monitor brand perception, and benchmark against competitors.
Not ideal if you need a general-purpose sentiment analysis tool for domains outside of telecommunications or if you lack the technical skills to run Python notebooks.
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Last pushed
Aug 12, 2024
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